Difference between revisions of "Publications/fouquier.07.gbr"
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{{Publication |
{{Publication |
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| date = 2007-02-15 |
| date = 2007-02-15 |
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| authors = Geoffroy Fouquier, Jamal Atif, Isabelle Bloch |
| authors = Geoffroy Fouquier, Jamal Atif, Isabelle Bloch |
Revision as of 15:51, 14 November 2013
- Authors
- Geoffroy Fouquier, Jamal Atif, Isabelle Bloch
- Where
- Proceedings of the 6th IAPR TC-15 Workshop on Graph-based Representations in Pattern Recognition (GBR)
- Place
- Alicante, Spain
- Type
- inproceedings
- Publisher
- Springer Verlag
- Keywords
- Image
- Date
- 2007-02-15
Abstract
Spatial relations play a crucial role in model-based image recognition and interpretation due to their stability compared to many other image appearance characteristics. Graphs are well adapted to represent such information. Sequential methods for knowledge-based recognition of structures require to define in which order the structures have to be recognized. We propose to address this problem of order definition by developing algorithms that automatically deduce sequential segmentation paths from fuzzy spatial attribute graphs. As an illustration, these algorithms are applied on brain image understanding.
Bibtex (lrde.bib)
@InProceedings{ fouquier.07.gbr, author = {Geoffroy Fouquier and Jamal Atif and Isabelle Bloch}, title = {Local reasoning in fuzzy attribute graphs for optimizing sequential segmentation}, booktitle = {Proceedings of the 6th IAPR TC-15 Workshop on Graph-based Representations in Pattern Recognition (GBR)}, year = 2007, month = jun, address = {Alicante, Spain}, volume = {LNCS 4538}, editor = {F. Escolano and M. Vento}, publisher = {Springer Verlag}, isbn = {978-3-540-72902-0}, pages = {138--147}, abstract = {Spatial relations play a crucial role in model-based image recognition and interpretation due to their stability compared to many other image appearance characteristics. Graphs are well adapted to represent such information. Sequential methods for knowledge-based recognition of structures require to define in which order the structures have to be recognized. We propose to address this problem of order definition by developing algorithms that automatically deduce sequential segmentation paths from fuzzy spatial attribute graphs. As an illustration, these algorithms are applied on brain image understanding.} }